unsubscribeCancel a subscription by id. Ownership is enforced — you can only cancel your own subscriptions. The row is deactivated (not deleted) so its historical events stay available via recent_alerts.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Subscription id (uuid) returned by subscribe. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds substantial behavioral detail beyond the annotations: ownership enforcement, the soft-delete behavior (deactivated not deleted), and the continued availability of historical events via recent_alerts. This meaningfully informs the agent about side effects, which is especially valuable given the mutation context (readOnlyHint=false).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each earning its place: the action, the ownership constraint, and the deactivation behavior. Front-loaded with the verb, no redundant filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple cancellation tool with one parameter and no output schema, this description is complete: action, constraint, side effect, and historical data implications. The annotations already cover idempotency and non-destructiveness, so the description does not need to repeat them.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers the id parameter with a clear description, so baseline is 3. The description adds crucial semantics by stating 'Ownership is enforced — you can only cancel your own subscriptions,' which tells the agent that the id must refer to the caller's own subscription. This extra context raises the score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Cancel') with a specific resource ('a subscription by id') and clearly distinguishes this from sibling tools like subscribe and list_subscriptions. The primary purpose is immediately understandable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: ownership is enforced, and cancellation is a deactivation rather than deletion. It implies when to use (you have a subscription you want to cancel) and mentions recent_alerts as a way to still access historical data, but it does not explicitly name alternatives or exclusion criteria beyond that.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools have unclear boundaries: ask_pipeworx and ask_pipeworx_beta are described as currently identical, and citation vs citations differ only by pluralization while actually accepting different ID types (OCI vs DOI). The server is named Opencitations but 31 of 37 tools serve unrelated purposes, so an agent cannot infer what the set is for without reading very long descriptions.
All names are snake_case and family prefixes (polymarket_*, ask_pipeworx_*, pipeworx_*) give some predictability. However, conventions are mixed: bare resource nouns (citation, citations, references, metadata) coexist with verb_noun tools (resolve_entity, validate_claim) and noun phrases (recent_changes, entity_profile, deep_research), so there is no single pattern that lets an agent predict tool names.
37 tools is well past the 25+ threshold for a heavy set, and most are redundant with the server's own router tools — ask_pipeworx already reaches 5,759 underlying tools, making many direct tools overlapping conveniences. The scope also wildly overshoots the server name: only 6 of 37 tools serve the Opencitations citation-graph domain.
For the named OpenCitations domain, the core citation-graph read operations exist (metadata, incoming citations, outgoing references, counts, OCI record lookup), but there is no paper/DOI discovery or search tool — an agent must already possess a DOI, a dead end for title/author queries. The broader accidental domain (data routing, company research, prediction markets, monitoring) is covered unusually well, but that does not serve the server's stated purpose.